Novel oracle constructions for quantum random access memory

TL;DR

This paper introduces new quantum oracle designs for quantum random access memory that leverage Walsh-Hadamard transforms, enabling efficient, low-depth, and low-connectivity implementations especially for functions with sparse transforms.

Contribution

The authors develop Walsh-Hadamard-based quantum oracle constructions with tunable ancilla use, improving efficiency for functions with sparse or low-degree Walsh-Hadamard transforms.

Findings

Oracle complexity scales with Walsh-Hadamard sparsity, not function sparsity.

Depth can be reduced to O(n + log(d/ε)) with ancilla trade-offs.

Efficient for functions with low approximate degree, like read-once formulas.

Abstract

We present new designs for quantum random access memory. More precisely, for each function, $f : \mathbb{F}_2^n \rightarrow \mathbb{F}_2^d$, we construct oracles, $\mathcal{O}_f$, with the property \begin{equation} \mathcal{O}_f \left| x \right\rangle_n \left| 0 \right\rangle_d = \left| x \right\rangle_n \left| f(x) \right\rangle_d. \end{equation} Our methods are based on the Walsh-Hadamard Transform of $f$, viewed as an integer valued function. In general, the complexity of our method scales with the sparsity of the Walsh-Hadamard Transform and not the sparsity of $f$, yielding more favorable constructions in cases such as binary optimization problems and function with low-degree Walsh-Hadamard Transforms. Furthermore, our design comes with a tuneable amount of ancillas that can trade depth for size. In the ancilla-free design, these oracles can be $\epsilon$-approximated so that the Clifford + $T$ depth is $O \left( \left( n + \log_2 \left( \tfrac{d}{\epsilon} \right) \right) \mathcal{W}_f \right)$, where $\mathcal{W}_f$ is the number of nonzero components in the Walsh-Hadamard Transform. The depth of the shallowest version is $O \left( n + \log_2 \left( \tfrac{d}{\epsilon} \right) \right)$, using $n + d \mathcal{W}_f$ qubit. The connectivity of these circuits is also only logarithmic in $\mathcal{W}_f$. As an application, we show that for boolean functions with low approximate degrees (as in the case of read-once formulas) the complexities of the corresponding QRAM oracles scale only as $2^{\widetilde{O} \left( \sqrt{n} \log_2 \left( n \right) \right)}$.